add infeasible cost tests, remove redundant scipyminimise maxiter opt…

…ions check

pybop/optimisers/scipy_optimisers.py

@@ -49,9 +49,10 @@ def _runoptimise(self, cost_function, x0, bounds):
             A tuple (x, final_cost) containing the optimized parameters and the value of `cost_function` at the optimum.
         """
 
-        # Add callback storing history of parameter values
         self.log = [[x0]]
+        self.options = {"maxiter": self._max_iterations}
 
+        # Add callback storing history of parameter values
         def callback(x):
             self.log.append([x])
 
@@ -74,12 +75,6 @@ def cost_wrapper(x):
                 (lower, upper) for lower, upper in zip(bounds["lower"], bounds["upper"])
             )
 
-        # Set max iterations
-        if self._max_iterations is not None:
-            self.options = {"maxiter": self._max_iterations}
-        else:
-            self.options.pop("maxiter", None)
-
         result = minimize(
             cost_wrapper,
             x0,
@@ -158,6 +153,8 @@ def _runoptimise(self, cost_function, x0=None, bounds=None):
             A tuple (x, final_cost) containing the optimized parameters and the value of ``cost_function`` at the optimum.
         """
 
+        self.log = []
+
         if bounds is None:
             raise ValueError("Bounds must be specified for differential_evolution.")
 
@@ -167,8 +164,6 @@ def _runoptimise(self, cost_function, x0=None, bounds=None):
             )
 
         # Add callback storing history of parameter values
-        self.log = []
-
         def callback(x, convergence):
             self.log.append([x])
 

tests/unit/test_cost.py

@@ -153,10 +153,10 @@ def test_costs(self, cost):
             for i in range(len(record)):
                 assert "Non-physical point encountered" in str(record[i].message)
 
-        if isinstance(cost, pybop.RootMeanSquaredError):
             # Test infeasible locations
             cost.problem._model.allow_infeasible_solutions = False
             assert cost([1.1]) == np.inf
+            assert cost.evaluateS1([1.1]) == (np.inf, cost._de)
 
         # Test exception for non-numeric inputs
         with pytest.raises(ValueError):